Basics of Econometrics — DU Bachelor of Business Administration (Financial Investment Analysis) Previous Year Question Papers

3. No negative marking. 5. Answer all questions. Question 1: For each of the following statements, indicate whether it is True or False, and provide a clear and rigorous justification. Responses without explanation or with incorrect reasoning will not be awarded any marks. 5x3 = 15 Marks 1. In multiple regression, adding more variables always improves the model? 2. Joint hypothesis testing examines multiple coefficients simultaneously? 3. Multicollinearity affects the unbiasedness of OLS estimators. 4. Heteroscedasticity leads to inefficient estimates and incorrect standard errors. 5. Endogeneity affects the unbiasedness of OLS estimators. Question 2: Consider the following regression equation, in regression equation researcher mark 1 for boys and 0 for girls: 15 Marks Dependent Variable: WEIGHT Included observations: 60 Variable Coefficient Std. Error It-Statistic Prob. FAMILY INCOME 0.016077 0.00743 2.163671 0.0348 DUMMY*FAMILY_INCOME -0.029963 0.011474 -2.611304 0.0116 A study is conducted to examine the relationship between family income and the weight of children, separately for boys and girls. Using regression analysis, the researcher aims to understand how changes in family income influence the weight of children. Based on the given data, answer the following questions: 1. Formulate the regression equations for boys and girls. 2. Interpret the slope coefficient for boys by calculating the change in weight associated with a one-unit increase in family income. 3. Interpret the slope coefficient for girls by calculating the change in weight associated with a one-unit increase in family income. 4. Estimate the expected weight of boys when family income is zero, and interpret its meaning. 5. Estimate the expected weight of girls when family income is zero, and interpret its meaning. 6. Estimate the expected weight of boys when family income is 100 units. 7. Estimate the expected weight of girls when family income is 100 units. Question 3: Regression Model: Wage_Rate-atB1xEducation_Years+B2xExperiencetError Term Given the following data: (15 Marks) Number of Observations (n): 60 Mean Sum of Squares of Regression (MSR): 10.245312 Mean Sum of Squares of Residual (MSE): 1.024531 Intercept (a) Coefficient: 6.982154321 Standard Error of Intercept: 0.812345672 Coefficient of Education_Years (Br): 0.152451236 Standard Error of BI: 0.041245678 Coefficient of Experience (Bz): 0.276543219 Standard Error of Bz: 0.065432187 1. Compute Multiple R. 2. Compute R° (Coefficient of Determination). 3. Compute Adjusted R?. • 4. Compute the Standard Error of Regression. 5. Based on the calculated t-statistics, Test whether the intercept, B (Education_Years), and Bz (Experience) are significantly different from zero at the 5% level of significance. Null Hypotheses: Question 4: A researcher is studying the factors influencing whether an individual purchases a health insurance policy. The dependent variable is binary: 15 Marks